arXiv:2606. 30429v1 Announce Type: new Abstract: Text-to-3D systems can now synthesize a mechanical part from a single sentence, yet the result is a shape to render, not a design to edit.
Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.
arXiv:2605. 28579v2 Announce Type: replace Abstract: Large language models (LLMs) have recently advanced text-driven 3D generation, yet Text-to-CAD remains far from supporting industrial product design.
VisCAD is a foundation model suite that tackles AI-assisted computer-aided design for industrial products, covering both part-level and assembly-level generation. Its core component, VisCAD‑M1, is a 27B model trained for part-level design generation and outperforms existing models on PubCADBench and RealCADBench, achieving a part-level score of 0.5540 and reaching 0.5797 when used as a test-time verifier. VisCAD also offers a domain-specific harness that improves complex assembly generation compared to general-purpose harnesses, showing quantitative and qualitative advantages.
CADKnitter is a compositional CAD generation framework that uses geometric-guiding cues to steer diffusion sampling, enabling the creation of complementary CAD parts that satisfy both geometric constraints of an existing model and semantic constraints from a text prompt. The authors introduce KnitCAD, a dataset of over 310,000 CAD models paired with textual prompts and assembly metadata to support training and evaluation. Experiments show that CADKnitter outperforms state‑of‑the‑art baselines by a clear margin.
arXiv:2609.07434v1 Announce Type: new Abstract: Natural-language Computer-Aided Design (CAD) code generation aims to turn design intent into executable and editable parametric programs. Large languag...
arXiv:2608.28669v1 Announce Type: new Abstract: Recovering an executable parametric CAD program from an observed object is fundamentally ambiguous, because the same final geometry can result from dif...
arXiv:2608. 05714v1 Announce Type: new Abstract: Text-to-CAD generation translates natural-language design intent into editable and executable parametric computer-aided design (CAD) codes, reducing the expertise and effort required for manual modeling.